Update app.py

app.py

@@ -4,65 +4,76 @@ import numpy as np
 from PIL import Image
 import json
 import uuid
-from pydrive2.auth import GoogleAuth
-from pydrive2.drive import GoogleDrive
-
-# --- Google Drive setup với Service Account ---
-gauth = GoogleAuth()
-gauth.ServiceAuth(settings_file="service_account.json")  # file JSON của service account
-drive = GoogleDrive(gauth)
-
-# ID folder public trên Google Drive
-FOLDER_ID = "1MwGdJbVbLNSLnmHrR-mGlH8EAJ3gy50R"
-
-# Dictionary lưu mapping image_id -> {'file_id':..., 'name':...}
-image_drive_map = {}
-
-# 1️⃣ Upload ảnh lên Google Drive
+import base64
+import pymongo
+from io import BytesIO
+
+# =======================
+# MongoDB setup
+# =======================
+client = pymongo.MongoClient(
+    "mongodb+srv://huyh01480_db_user:OGNNUaT14nlYh2Uu@cluster0.n8pboqq.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0"
+)
+db = client["faceDB"]
+face_collection = db["faceImg"]
+
+# =======================
+# Upload ảnh + lưu MongoDB
+# =======================
 def upload_image(image, name):
     try:
         if isinstance(image, Image.Image):
             image = np.array(image)
+
         image_id = str(uuid.uuid4())
-        filename = f"{image_id}.png"
         pil_image = Image.fromarray(image)
-        pil_image.save(filename)  # tạm lưu local
-
-        gfile = drive.CreateFile({'title': filename, 'parents':[{'id': FOLDER_ID}]})
-        gfile.SetContentFile(filename)
-        gfile.Upload()
+        buffer = BytesIO()
+        pil_image.save(buffer, format="PNG")
+        img_bytes = buffer.getvalue()
+        img_base64 = base64.b64encode(img_bytes).decode('utf-8')
+
+        # Lưu vào MongoDB
+        doc = {
+            "_id": image_id,
+            "name": name,
+            "image": img_base64
+        }
+        face_collection.insert_one(doc)
 
-        image_drive_map[image_id] = {'file_id': gfile['id'], 'name': name}
-        file_link = f"https://drive.google.com/file/d/{gfile['id']}/view?usp=sharing"
-        return f"Ảnh lưu thành công với ID: {image_id}\nTên: {name}\nLink: {file_link}", image_id
+        return f"✅ Upload thành công!\nID: {image_id}\nTên: {name}", image_id
     except Exception as e:
-        return f"Lỗi khi upload: {str(e)}", None
+        return f"❌ Lỗi upload: {str(e)}", None
 
-# 2️⃣ Nhận diện khuôn mặt
+# =======================
+# Nhận diện khuôn mặt
+# =======================
 def recognize_face(image, image_id):
     try:
-        if image_id not in image_drive_map:
-            return "Ảnh ID không tồn tại"
+        doc = face_collection.find_one({"_id": image_id})
+        if not doc:
+            return "❌ Ảnh ID không tồn tại"
+
+        # Decode base64 từ MongoDB
+        img_bytes = base64.b64decode(doc['image'])
+        pil_image = Image.open(BytesIO(img_bytes))
+        img2 = np.array(pil_image)
+
         if isinstance(image, Image.Image):
             image = np.array(image)
 
-        # Download ảnh từ Drive
-        file_id = image_drive_map[image_id]['file_id']
-        stored_name = image_drive_map[image_id]['name']
-        gfile = drive.CreateFile({'id': file_id})
-        gfile.GetContentFile(f"temp_{image_id}.png")
-
-        result = DeepFace.verify(img1_path=image, img2_path=f"temp_{image_id}.png")
+        result = DeepFace.verify(img1_path=image, img2_path=img2)
         output = {
             "Verified": result["verified"],
             "Khoảng cách": round(result["distance"], 4),
-            "Tên ảnh gốc": stored_name
+            "Tên ảnh gốc": doc['name']
         }
         return json.dumps(output, ensure_ascii=False, indent=2)
     except Exception as e:
-        return f"Lỗi khi nhận diện: {str(e)}"
+        return f"❌ Lỗi nhận diện: {str(e)}"
 
-# 3️⃣ Phân tích khuôn mặt
+# =======================
+# Phân tích khuôn mặt
+# =======================
 def analyze_face(image):
     try:
         if isinstance(image, Image.Image):
@@ -81,11 +92,13 @@ def analyze_face(image):
         }
         return json.dumps(output, ensure_ascii=False, indent=2)
     except Exception as e:
-        return f"Lỗi khi phân tích: {str(e)}"
+        return f"❌ Lỗi phân tích: {str(e)}"
 
-# --- Gradio interface ---
+# =======================
+# Gradio interface
+# =======================
 with gr.Blocks() as demo:
-    gr.Markdown("## 📁 Upload ảnh lên Google Drive")
+    gr.Markdown("## 📁 Upload ảnh vào MongoDB")
     with gr.Row():
         upload_input = gr.Image(label="Upload ảnh", type="numpy")
         name_input = gr.Textbox(label="Tên người trong ảnh")